confint.tulpa_fit: Credible intervals for the fixed effects

In tulpa: Templated Unified Library for Posterior Approximation in Bayesian Hierarchical Models

Credible intervals for the fixed effects

Description

Credible intervals for the fixed effects

Usage

## S3 method for class 'tulpa_fit'
confint(object, parm = NULL, level = 0.95, ...)

Arguments

object	A tulpa_fit object.
parm	Parameter names or indices (default: all fixed effects). Indices address the fixed effects. A name that is not a fixed effect is read off the fit's posterior draws when they carry a column of that name (for example a sampler's log_sigma_re), as their equal-tailed quantile interval; any other name is an error.
level	Interval level, a single number in ⁠(0, 1)⁠ (default 0.95).
...	Ignored.

Value

Matrix with lower and upper columns, labelled as stats::confint.default() labels them ("2.5 %" and "97.5 %" at the default level). A nested-Laplace fit carries interval_source / interval_declined (which read produced the bounds – by default the grid's Gaussian-mixture CDF), retained_mass (the share of the grid weight the bounds are conditional on), and skew_applied, one logical per reported coefficient saying whether its bounds are the inner-Laplace skew-corrected quantiles or not. See summary.tulpa_fit().

tulpa documentation built on Oct. 19, 2026, 5:09 p.m.